Nash | Second Mind

Governed AI systems, agent reliability, evals and workflow implementation. Building bounded, testable AI for real-world work.

[Nash | Second Mind @Secondmindsys]

What part of your AI workflow or system do you keep correcting, working around, or trying to make more reliable?

AI can produce the work and still leave you doing the hard part: correcting it, checking it, constraining it, and figuring out what should happen next.

That’s the gap Second Mind Systems works on.

Maybe an agent goes beyond scope.
Maybe instructions don’t hold consistently.
Maybe the workflow behaves differently from run to run.
Maybe you don’t have good evals for deciding whether the AI is actually doing the right thing.

We work across:

• AI workflow diagnostics
• Agent reliability audits
• Eval design
• Behavior and control specifications
• Workflow implementation
• Strategy development
• Governed AI systems

Right now, I’m opening the first 10 Behavior Profile Lab engagements as a bounded way to work with us.

Bring one recurring problem in one AI workflow or system, along with real examples of what keeps happening.

We reconstruct the problem from evidence, identify the recurring failure, define the behavior and boundaries you need, create the appropriate control or specification when warranted, and provide evaluation cases and a clear path for applying the result.

For a problem that fits the Lab, this is the complete bounded engagement—not a consultation that merely tells you what to buy next.

If the outcome requires hands-on code changes, integrations, deployment, or live-system work, we identify that as a separate scope rather than pretending the Lab covers unlimited implementation.

Founding Lab offer: $200 for one qualifying bounded engagement.
First 10 only.

Public proof:

Governed AI Systems Portfolio

https://t.co/fmTjnnxkiu

PBM Contract Analysis

I analyzed Mark Cuban’s open-source PBM contract and built a control-design contribution around how its protections survive procurement and implementation. Mark Cuban reposted the contribution on LinkedIn.

Read the contribution:

https://t.co/bsv5hRo8EZ

Mark Cuban’s Repost — LinkedIn reshare panel:

https://t.co/BL9ViTLWki

Governed Change Demo

https://t.co/zble1kdP0D

Connect on LinkedIn:

https://t.co/DJIulKjbKI

If there’s something in your AI workflow or system you keep correcting, working around, or trying to make more reliable, DM me or email [email protected] with a short description of what keeps happening.

Please don’t send credentials, private code, sensitive records, or other confidential material in your first message.

[Nash | Second Mind @Secondmindsys]

@grok Using gstack’s current README and changelog, show three practical use cases for someone returning after a few months:

A founder planning a feature before building.
A developer reviewing and testing an existing change.
A maintainer identifying redundant or low value tests.

For each, explain where to start, which commands apply, what information to provide, and what result to expect. Include a copy ready starting prompt and link the relevant docs. Note any setup requirements or decisions that still need human input. Explain in plain English.

[Nash | Second Mind @Secondmindsys]

There’s still a skill in knowing what to ask, how to frame the problem, what context to provide, what the AI can figure out itself, and what needs to be worked out together.

As models improved, they can take on more of that work. That changes how we design/structure the interaction, and sometimes how much instruction we need.

[Nash | Second Mind @Secondmindsys]

@dr_ent247 @VraserX Tbh, I’m not surprised. Im pretty sure you used Astra? Even Astra on low is unusable. I don’t touch Astra at all for anything anymore. Sol 6.1.

[Nash | Second Mind @Secondmindsys]

Yeah. I only use Codex as an adversarial reviewer and for computer use. I’m a grand fathered $200 pro user. At the end of this month, I may actually let my $200 pro account downgrade to a plus account and just live off my 62k grand fathered API credits and bump my Max Claude from $100 to a $200 subscription.

[Nash | Second Mind @Secondmindsys]

@jonzzy I really want to go mining/tailoring or tailoring/enchanting. But rolling on a PVP server, and my love for PVP… I won’t be able to help but go mining/engineering.

[Nash | Second Mind @Secondmindsys]

@Trencheiro Ironforge is my favorite. Thunderbluff has the best and most practical layout. Everything is so easily accessible.

[Nash | Second Mind @Secondmindsys]

@jonzzy Teldrassil and Tirisfal Glades

[Nash | Second Mind @Secondmindsys]

One person’s productivity gain can become everyone else’s new baseline.

As AI lets some people accomplish more in the same amount of time, employers and customers may start expecting more from everyone.

Someone could become twice as productive and still end up working the same hours because the expectations around them have changed.

[Nash | Second Mind @Secondmindsys]

I think one of the biggest things Cost Plus Drugs can change is what employers are willing to accept without an explanation.

When there’s a clear price they can compare against, they can go back to their PBM and ask where the difference comes from. How much is paying for the medication, how much covers actual services, and what are they getting for those extra costs? Clear pricing gives employers leverage to demand an explanation of where their money goes and what services justify the cost.

The more employers can ask those questions with real numbers in front of them, the harder it becomes for unexplained pricing to go unquestioned.

[Nash | Second Mind @Secondmindsys]

Your team’s next AI use case may be sitting in the review queue.

This prompt uses your delivery history to find where work waits and what could help it move.

Give this to your agent:

“Using the issue, pull request, CI and deployment records I provide or authorize you to inspect, map a sample of recent changes from work started to production.

Separate active work from waiting wherever the evidence allows. Show where changes accumulate, return for rework or repeatedly fail checks. Don’t treat all elapsed time as working time.

Identify the strongest supported bottleneck. Recommend one small intervention, explaining whether AI could help and what constraint would remain.

Define how we would compare delivery time, review effort and escaped defects before and after. Flag missing evidence and alternative explanations.

Keep the investigation read-only. Don’t change workflows or settings.”

Use the findings to decide where to put the next hour of automation work.

[Nash | Second Mind @Secondmindsys]

@Ionkosm Let me guess. You ran out of tokens?

[Nash | Second Mind @Secondmindsys]

Oof lol. Before resetting anything, I’d check what Codex was actually failing to load. You might be able to recover it without losing your workspace setup.

If you have another working local agent:

Give this to your agent:

“Help me diagnose the Codex desktop error ‘Couldn’t load workspace settings.’

Using existing authorized access, inspect relevant logs around the failure time at ~/Library/Logs/com.openai.codex/, along with the installed app version and basic environment details.

Identify the actual errors, distinguish confirmed findings from possible causes, and recommend the smallest supported recovery step.

Start read-only. Don’t delete or reset files, change settings, reinstall anything or interrupt running work without my approval.

Show me how to verify whether the fix worked. Redact sensitive log details before sharing.”

If you don’t have another local agent, you can give redacted log excerpts to another assistant.

[Nash | Second Mind @Secondmindsys]

@ChrisGPT Waiting eagerly.

[Nash | Second Mind @Secondmindsys]

The possibility of turning one element into gold could actually help make fusion energy commercially viable.

The proposed reaction uses fusion neutrons to transform mercury into gold, while also producing neutrons that can help breed more fusion fuel. That fuel could help start additional reactors.

Revenue from the gold could help finance those reactors as they generate electricity.

If it scales, the ancient ambition of alchemy could help finance abundant energy. We are definitely living in incredible times.

[Nash | Second Mind @Secondmindsys]

@grok Look into what Mark Cuban is proposing here. Based on his public statements and available reporting, what problem is he trying to solve, and why might solving it matter for people with rare diseases?

Go beyond describing the announcement. Explain what could change if the approach works, what currently makes these treatments difficult to bring to patients, and what remains uncertain.

Separate his stated goals from your interpretation, consider alternative readings, and distinguish demonstrated results from ambitions. Cite what you can verify and say if the full article isn't accessible.

[Nash | Second Mind @Secondmindsys]

How will Anthropic recognize when safety can no longer keep pace with capability development?

What observable signs would indicate that gap, and who determines when it’s serious enough to change development or deployment plans?

You’ve already described external review and changes to the RSP. Making the conditions for shifting from racing to pacing explicit ahead of time would give the public something concrete to evaluate when competitive pressure is highest.

[Nash | Second Mind @Secondmindsys]

I think there's a lot of potential in searching for people based on what they've actually experienced, rather than just their job title or who they work for.

A few ways founders could use Happenstance:

1. Find people who've already tried your idea.
Learn what they ran into before committing months to building.

Give this to your agent:

“Using Happenstance, find people in my accessible network with documented experience attempting something similar to [idea]. Show what makes each person relevant, the available introduction path, and what we still don't know.”

2. Find potential customers who understand the problem.
Talk to people dealing with the specific issue you're trying to solve.

Give this to your agent:

“Search Happenstance for people whose documented work relates to [problem]. Prioritize relevant experience over job titles. Show the evidence for each match and any known warm introduction path.”

3. Find someone who's handled the transition you're facing.
For example, taking a product from its first customers into a repeatable business.

Give this to your agent:

“Find people in my Happenstance network with experience navigating [specific business transition]. Explain why each might be relevant and how we're connected. If no supported path exists, say so.”

These assume your agent has Happenstance connected. Otherwise, paste the searches into Happenstance directly.

[Nash | Second Mind @Secondmindsys]

One important case for adaptive permissions is when an agent was legitimately authorized, but the risk changes while it’s working.

Say an agent has approval to access a dataset, then new evidence makes that access unsafe while several actions are still queued.

Can the system stop those pending actions, preserve what already happened, and establish what must be verified before work resumes?

Permission granted at the start shouldn’t stay valid after the conditions that justified it have changed.

[Nash | Second Mind @Secondmindsys]

Containment needs to reach beyond the agent that started the work.

An agent might have legitimate permission when a task begins, then delegate work or queue actions before that permission is revoked.

What happens to everything already in motion?

A demonstration worth showing: revoke the original agent mid task, then verify whether its delegated agents and pending actions stop too, including work running under another identity.

That’s where we can see whether revocation actually contains the execution.